Liveness detection is crucial in the identity verification process, as it identifies deepfake or identity theft attacks by distinguishing between a genuine user and a fraudulent identity. 3D liveness detection is becoming more prevalent and integrated into our daily routines, particularly in the context of using smartphones for identity verification. Face liveness checks are being used for identity verification in various sectors, including law enforcement, security management, healthcare, entertainment, and finance, due to their precision and effectiveness.
A scientist Alan Turing introduced machine learning algorithms with their ability to check liveness. In 1950, he experimented with the term “liveness detection” for the first time and conducted an experiment known as “Alan Turing.” He assessed the capability of machine algorithms to generate false human responses and concluded that human features and responses can be replicated.
Working Principle
3D liveness is a reliable method of authentication that permits access only to real individuals while effectively identifying fraudulent identities, including spoofed attacks, deepfakes, and morphed attacks. It utilizes a range of methods and algorithms to operate effectively and protect against fraudulent identities.
- Machine Learning
To authenticate identities within seconds, biometric liveness detection incorporates sophisticated and advanced AI algorithms. Due to the extensive training on a vast number of identities, the algorithms can process data rapidly and accurately authenticate real individuals. Moreover, irregularities are identified quickly, which complicates the efforts of cybercriminals to evade authentication mechanisms and gain unauthorized access to systems.
- Motion Analysis
Biometric face liveness detection employs motion analysis methods to authenticate identities by minutely analyzing certain movements by individuals. For instance, during liveness detection, individuals are asked to smile, blink, or move heads in a specific direction which a genuine individual can perform easily, however, a static image or live video wouldn’t be able to replicate certain movements or behavioral patterns.
- Texture Analysis
The fine details of skin texture including wrinkles skin color, pores, and even dryness are analyzed to authenticate individuals, leaving cybercriminals with no chance to replicate these little details. Spoofing attacks like silicone masks or rubber attacks don’t contain minute details of skin texture, making it effortless for biometric authentication technology to detect fabricated identities. Texture analysis is a robust method used in passive liveness detection and doesn’t mandate live user interactions to verify the identity.
- Depth Sensing
3D depth sensing plays a crucial role in biometric identity verification by analyzing the three-dimensional key points or facial attributes of individuals including shape, contour, and structure of face unique to each human being. This technique effectively distinguishes between real and fake identities by capturing and analyzing three-dimensional attributes, detecting anomalies swiftly. 3D depth sensing adds an extra layer of security to authentication, owing to its high accuracy and reliability.
- Challenge Response Test
This method of biometric liveness detection requires the person sitting in front of the camera attempting to log in to systems, to perform certain actions to show his liveness. As liveness detection technology authenticates individuals by analyzing the movement and behavior of live individuals, so challenge-response test verifies the identities based on movements and detects anomalies in very little time. Sometimes, it also requires the real-time analysis of an individual which includes performing actions like smiling, blinking, and more.
Conclusion
Liveness detection technology comes forth as a robust and accurate tool employed in facial recognition technology to effectively authenticate individuals. The advanced tool plays a crucial role in fighting the rising threats of deepfakes or spoofed attacks by analyzing the movements and behavior of the individual attempting to get access to systems. It also adds extra layers of security and finds astonishing applications in various sectors globally apart from ID verification including healthcare, retail, e-commerce, and law enforcement. Besides, liveness check KYC is also helpful in smart and safe onboarding of the employees.
